ShieldLabs is a visitor identification and traffic quality scoring platform that analyzes device and network signals to identify multi-accounting, account takeovers, and fraudulent traffic.
What the product does and how it is positioned
ShieldLabs is fraud detection and prevention with traffic quality scoring. It detects users running multiple accounts, account sharing and takeovers under any masking, so you prevent losses from free-trial, bonus, promo and API abuse. More than 100 device and network signals are collected on every visit and cross-checked against each other, which exposes deep masking with 99.9% identification accuracy. Visitors, users, devices and IP addresses are identified and scored, risk signals such as VPN, proxy, Tor and anti-detect browsers are returned by name, and bot and AI agent traffic is detected. It is built for developers and growth teams at SaaS, fintech, ecommerce and gaming companies: install a JavaScript snippet in about five minutes, then use the risk score through the API and webhooks. Self-serve pricing starts with a free plan of 5,000 identifications, paid plans from 99 USD per month.
ShieldLabs inspects visitor traffic by analyzing over 100 device, operating system, browser, and network data points during page load. The system generates a persistent identifier designed to recognize users across cleared cookies, rotated IP addresses, and private browsing sessions.
The service evaluates traffic using explainable risk scoring and preconfigured pattern detection for issues such as account sharing, multi-accounting, and click fraud. Data payloads containing visitor IDs, risk scores, and anonymity attributes are delivered via API and webhooks for programmatic enforcement.
Source-supported ways to use the product
Teams evaluate the proportion of invalid, anonymous, or datacenter clicks across acquisition channels and UTM parameters to assess ad traffic quality.
Platforms identify individuals attempting to generate multiple accounts or farm sign-up bonuses and referral credits from the same device using fresh emails or incognito mode.
Services detect unauthorized access attempts involving credential stuffing, proxies, or anti-detect browsers, as well as single subscription accounts distributed across multiple geographic locations.
Organizations recognize legitimate returning visitors on their initial request without imposing repetitive verification steps or unnecessary friction.
The documented workflow, where available
Add the ShieldLabs JavaScript snippet into the web application, framework, or content management system header.
ShieldLabs collects client-side device, OS, browser, and network data points upon page load to generate a persistent visitor identifier and evaluate anonymity signals.
ShieldLabs returns the persistent visitor ID, 0 to 100 risk score, and detailed detection flags to customer servers via API responses or webhooks.
Customer backend code inspects the risk score and signal breakdown to permit, challenge, or restrict the session according to internal security rules.
ShieldLabs assesses each visitor interaction by aggregating device characteristics, browser automation markers, and network intelligence into an explainable score from 0 to 100. Rather than functioning as an uninspectable rating, the score includes the precise contributing components, such as detected proxies, timezone mismatches, and anti-detect browsers.
These signals are paired with preconfigured pattern detection running over historical traffic records. The pattern engine evaluates accounts and devices against common abuse models, including ban evasion and account farms, categorizing identified issues by severity.
Human-maintained commercial information
Pricing can change. Confirm the current plan and billing terms on the official site before purchasing.
Checks to run with your own material and workflow
What was checked and when
Answers based on the source-checked product record
ShieldLabs is a fraud detection and traffic quality assessment platform that identifies visitors, detects anonymity techniques, and assigns risk scores to traffic.
ShieldLabs gathers more than 100 device, operating system, browser, IP, and network data points on the initial page load to generate a persistent visitor identifier across sessions and incognito modes.
It detects signals including VPNs, proxies, Tor, privacy relays, datacenter IPs, IP mismatches, anti-detect browsers, operating system tampering, browser automation, and geolocation spoofing.
No, ShieldLabs does not enforce blocks directly. It supplies risk scores, anonymity signals, and identifiers through its API and webhooks, allowing customer applications to apply custom business rules.
ShieldLabs is installed via a client-side JavaScript snippet and integrates with web frameworks, content management systems, and backend services through REST APIs and webhooks.
